mock

A command that creates a practice exam based on a course's past homework and section coverage. It saves the problems and a separate hidden solution file for later grading.

In plain words
What is it for?
Use it to generate a timed mock exam, optionally emphasizing selected sections, then solve and submit it through the grading workflow.
Why use it?
It provides practice that follows the course's apparent structure and emphasis instead of using an unrelated exam format. Students can solve it on paper and submit a PDF for grading.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/optimeta/paideia/mock
Clone the repo
git clone --depth 1 https://github.com/OPTIMETA/PAIDEIA
Per session 37 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 681 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.00681
Opus 5 $0.00018 $0.00341
Sonnet 5 $0.00007 $0.00136
Haiku 4.5 $0.00004 $0.00068

Measured 2d ago against content hash 2aa82edae8db, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mock scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/paideia/commands/mock.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Output language

Read INTERFACE_LANG from .course-meta (default en). All user-facing prose must be in that language. Keep in English regardless: file paths, slash command names, pattern IDs, LaTeX, tier markers, and the mock exam's structural labels (# Mock Exam — <date>, **Duration**, **Total**, ## P<n>).

Load skills/exam-drill/SKILL.md. Read course-index/summary.md, course-index/patterns.md, course-index/coverage.md.

Arguments: $ARGUMENTS (First token: minutes. Remaining: optional emphasize=... list.)

Procedure:

  1. Infer exam structure from coverage.md and past HW:

    • Typical mid/final: 4–6 problems, 2 hours
    • HW-weighted mix. Problems are drawn in proportion to HW density of each section. Rough target:
      • ≥70% of points from 🔥🔥 Exam-primary sections (3+ HW)
      • ~25% from 🔥 Exam-likely (2 HW)
      • ≤5% from 🟡 Exam-possible (1 HW)
      • 0% from ⚪ Low-risk (no HW) — do not invent problems in sections the professor never tested.
    • If user passed emphasize=§X,§Y, bias toward those (override the HW weighting if they override explicitly).
    • Difficulty distribution: 1 warmup / N-2 standard / 1 hard (multi-pattern)
  2. Design the exam:

    • For each problem, pick: target §, target pattern(s), point value, estimated time
    • Ensure patterns from ≥3 different parts of the course appear (tests integration)
    • Last problem should require chaining ≥2 patterns
  3. Save:

    • Problems → mock/exam_<ts>.md
    • Solutions → mock/exam_<ts>_sol.md (do not display)
  4. Print to chat:

    • The full exam (problem statements with point values and time suggestions)
    • Total points summing to 100 (or inferred weighting)
    • Closing line (in $INTERFACE_LANG): "Timer: $ARGUMENTS min. Solve on paper, upload as answers/mock_<ts>.pdf, then /grade."
  5. Do NOT reveal which patterns are being tested in the problem statements. The user should identify them during solving.

Exam format

# Mock Exam — <date>

**Duration**: <minutes> min  **Total**: 100 pts

---

## P1 (<pts>, ~<min> min)

<problem>

## P2 (<pts>, ~<min> min)

<problem>

...

Read the full file on GitHub · 64 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 64 lines · 37 tokens per session scan A 2aa82edae8db

Subscribe to this mod's changes

mock is a command published in the GitHub repository OPTIMETA/PAIDEIA (91 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 681 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.